A driverless vehicle (also known as “autonomous vehicle”, “self-driving vehicle” and “robotic vehicle”) is a vehicle that is capable of sensing its environment and navigating without human input.
The idea of driverless cars was predicted by many science fiction and non-science fiction writers a long time ago. In recent years, this idea has been actualized, with many auto makers and research groups building such cars and conducting experiments with them.
Publications about self-driving cars include (i) “INSIDE GOOGLE'S QUEST TO POPULARIZE SELF-DRIVING CARS,” By Adam Fisher, Popular Science (Posted Sep. 18, 2013) about Google's driverless car, and (ii) “NASA AND NISSAN JOIN FORCES TO BUILD SELF-DRIVING VEHICLES FOR EARTH AND SPACE” by Alex Davies, Wired.com (Posted Jan. 8, 2015) about Nissan's and NASA's driverless car.
The term driverless or autonomous motor-vehicles also includes semi-autonomous vehicles where a human driver may be available inside the motor-vehicle and may intervene with or take control of the driving if he so decides, as long as the motor-vehicle has a fully autonomous mode in which it navigates and drives without human input.
Obviously, a major concern with driverless cars is the avoidance of accidents where two or more cars are involved in a collision. The challenge is especially difficult under heavy traffic conditions, when many cars are driving in a convoy, continuously braking, decelerating and accelerating according to traffic events and road conditions.
First attempts for developing a driverless car relied on equipping the car with sensors capable of detecting events in all directions. For example, front-looking cameras and proximity sensors residing within a given car may monitor the car in front of it, looking for an indication it is braking or otherwise slowing down. If such an event is detected, and there is a danger of the given car hitting the car in front of it, the driving logic automatically slows down the given car or even brings it to a complete stop. Independently of that, rearward-looking cameras and proximity sensors are watching the car behind the given car, looking for an indication it is accelerating. If such an event is detected, and there is a danger of the given car being hit by the car behind it, the driving logic automatically accelerates the given car or otherwise maneuvers it to avoid being hit. Additional cameras and sensors may be directed sideways so as to watch for potential dangers from other directions.
It was soon found out that relying only on a car's own sensors is not good enough. If the car behind us is accelerating, it takes some time before the driving logic in our car knows about the event because of the time required for the sensors and the signal processing circuitry to identify it. As avoiding an accident depends on a quick response by our car, the time lost while identifying a traffic event might be crucial.
The solution adopted for solving the above problem is to have each car wirelessly transmit information about itself so that adjacent cars can receive that information and use it for taking their decisions. For example, when a driver starts to press down on his braking pedal the car immediately reports this event by transmitting a braking alert, without waiting for the braking process to actually slow down the car. The car immediately behind the braking car does not have to wait until its sensors detect an actual slowdown of the car in front of it or a lighting of its braking lights but can immediately reduce its speed based on the received alert. This way the response time available for a car to avoid an accident is longer and the risk of unavoidable accidents is reduced. In addition to reporting braking status a car may also report its location, its speed, its acceleration, failures it may have and other information that may be useful for other cars for assessing their risks and taking their decisions.
Typically driverless cars only listen to information from the car in front of them, considering it to be the main source of danger. In such case the communication is established only between adjacent cars in the traffic line (See for example “Broadband vehicle-to-vehicle communication using an extended autonomous cruise control sensor,” By Heddebaut et al, Published 17 May 2005). Some driverless cars may utilize information available from any car in their vicinity, even non-adjacent ones, but this is typically limited to alerts about road conditions and traffic events occurring ahead.
FIG. 1 illustrates a convoy of motor-vehicles, where a vector of travel (i.e. direction, magnitude) is illustrated by arrows. In the example of FIG. 1 all vehicles are travelling at the same speed and in the same direction. In the example of FIG. 1, (i) vehicle 100B is behind and follows vehicle 100A and (ii) vehicle 100C is behind and follows vehicle 100B; (ii) vehicle 100D is behind and follows vehicle 100C.
FIGS. 2A-2B illustrate one example of an accident between motor-vehicles 100A, 100B—FIG. 2A corresponds to an earlier moment in time before the accident occurs and
FIG. 2B illustrate the moment immediately after the collision between motor-vehicles 100A, 100B.
FIGS. 3A-3D illustrate a very specific type of accident—a chain accident. In FIG. 3A, first 100A and second 100B vehicles are stopped and waiting at a stop sign as a third vehicle 100C approaches from behind. In FIG. 3B, the third vehicle 100C hits the second vehicle 100B from behind, imparting to the second vehicle 100B forward momentum (Illustrated in FIG. 3C). In FIG. 3D, as a result of this forward momentum, second vehicle 100B hits first vehicle 100A from behind.
Intoxicated Drivers
Intoxicated drivers, otherwise known as ‘drunk drivers,’ are a scourge on our society. According to the National Highway Traffic Safety Administration, drunk driving involvement in fatal crashes in 2014 was almost four times higher at night than during the day (34 versus 9 percent).
US 20140297111, incorporated herein by reference in its entirety, discloses a vehicle control system comprising: an alcohol detector which detects an alcohol intake level of a driver of a vehicle; and a controller which controls the alcohol detector so that a detection of the alcohol intake level is started during a run of the vehicle just after the vehicle starts up and initially moves, wherein the controller determines whether the driver is a drunk person based on a detection result obtained from the alcohol detector, and wherein the controller stops the vehicle when the controller determines that the driver is the drunk person.
US 20140365142, incorporated herein by reference in its entirety, discloses wearable alcohol sensor that measures a user's blood alcohol level by detecting an amount of alcohol in the user's insensible perspiration.